Haptically Quantifying Young's Modulus of Soft Materials Using a Self-Locked Stretchable Strain Sensor

Biomimetic bimodal haptic perception using triboelectric effect

Multimodal haptic perception is essential for enhancing perceptual experiences in augmented reality applications. To date, several artificial tactile interfaces have been developed to perceive pressure and precontact signals, while simultaneously detecting object type and softness with quantified modulus still remains challenging. Here, inspired by the campaniform sensilla on insect antennae, we proposed a hemispherical bimodal intelligent tactile sensor (BITS) array using the triboelectric effect. The system is capable of softness identification, modulus quantification, and material type recognition. In principle, due to the varied deformability of materials, the BITS generates unique triboelectric output fingerprints when in contact with the tested object. Furthermore, owing to the different electron affinities, the BITS array can accurately recognize material type (99.4% accuracy), facilitating softness recognition (100% accuracy) and modulus quantification. It is promising that the BITS based on the triboelectric effect has the potential to be miniaturized to provide real-time accurate haptic information as an artificial antenna toward applications of human-machine integration.

Biomimetic Multimodal Receptors for Comprehensive Artificial Human Somatosensory System

Electronic skin (e-skin) capable of acquiring environmental and physiological information has attracted interest for healthcare, robotics, and human-machine interaction. However, traditional 2D e-skin only allows for in-plane force sensing, which limits access to comprehensive stimulus feedback due to the lack of out-of-plane signal detection caused by its 3D structure. Here, a dimension-switchable bioinspired receptor is reported to achieve multimodal perception by exploiting film kirigami. It offers the detection of in-plane (pressure and bending) and out-of-plane (force and airflow) signals by dynamically inducing the opening and reclosing of sensing unit. The receptor's hygroscopic and thermoelectric properties enable the sensing of humidity and temperature. Meanwhile, the thermoelectric receptor can differentiate mechanical stimuli from temperature by the voltage. The development enables a wide range of sensory capabilities of traditional e-skin and expands the applications in real life.

Skin-Inspired Multi-Modal Mechanoreceptors for Dynamic Haptic Exploration

Active sensing is a fundamental aspect of human and animal interactions with the environment, providing essential information about the hardness, texture, and tackiness of objects. This ability stems from the presence of diverse mechanoreceptors in the skin, capable of detecting a wide range of stimuli and from the sensorimotor control of biological mechanisms. In contrast, existing tactile sensors for robotic applications typically excel in identifying only limited types of information, lacking the versatility of biological mechanoreceptors and the requisite sensing strategies to extract tactile information proactively. Here, inspired by human haptic perception, a skin-inspired artificial 3D mechanoreceptor (SENS) capable of detecting multiple mechanical stimuli is developed to bridge sensing and action in a closed-loop sensorimotor system for dynamic haptic exploration. A tensor-based non-linear theoretical model is established to characterize the 3D deformation (e.g., tensile, compressive, and shear deformation) of SENS, providing guidance for the design and optimization of multimode sensing properties with high fidelity. Based on SENS, a closed-loop robotic system capable of recognizing objects with improved accuracy (≈96%) is further demonstrated. This dynamic haptic exploration approach shows promise for a wide range of applications such as autonomous learning, healthcare, and space and deep-sea exploration.

Intuition-and-Tactile Bimodal Sensing Based on Artificial-Intelligence-Motivated All-Fabric Bionic Electronic Skin for Intelligent Material Perception

Developing electronic skins (e-skins) with extraordinary perception through bionic strategies has far-reaching significance for the intellectualization of robot skins. Here, an artificial intelligence (AI)-motivated all-fabric bionic (AFB) e-skin is proposed, where the overall structure is inspired by the interlocked bionics of the epidermis-dermis interface inside the skin, while the structural design inspiration of the dielectric layer derives from the branch-needle structure of conifers. More importantly, AFB e-skin achieves intuition sensing in proximity mode and tactile sensing in pressure mode based on the fringing and iontronic effects, respectively, and is simulated and verified through COMSOL finite element analysis. The proposed AFB e-skin in pressure mode exhibits maximum sensitivity of 15.06 kPa-1 (<50 kPa), linear sensitivity of 6.06 kPa-1 (50-200 kPa), and fast response/recovery time of 5.6 ms (40 kPa). By integrating AFB e-skin with AI algorithm, and with the support of material inference mechanisms based on dielectric constant and softness/hardness, an intelligent material perception system capable of recognizing nine materials with indistinguishable surfaces within one proximity-pressure cycle is established, demonstrating abilities that surpass human perception.

Self-Adaptive Perception of Object's Deformability with Multiple Deformation Attributes Utilizing Biomimetic Mechanoreceptors

The perception of object's deformability in unstructured interactions relies on both kinesthetic and cutaneous cues to adapt the uncertainties of an object. However, the existing tactile sensors cannot provide adequate cutaneous cues to self-adaptively estimate the material softness, especially in non-standard contact scenarios where the interacting object deviates from the assumption of an elastic half-infinite body. This paper proposes an innovative design of a tactile sensor that integrates the capabilities of two slow-adapting mechanoreceptors within a soft medium, allowing self-decoupled sensing of local pressure and strain at specific locations within the contact interface. By leveraging these localized cutaneous cues, the sensor can accurately and self-adaptively measure the material softness of an object, accommodating variations in thicknesses and applied forces. Furthermore, when combined with a kinesthetic cue from the robot, the sensor can enhance tactile expression by the synergy of two relevant deformation attributes, including material softness and compliance. It is demonstrated that the biomimetic fusion of tactile information can fully comprehend the deformability of an object, hence facilitating robotic decision-making and dexterous manipulation.

Computational design of ultra-robust strain sensors for soft robot perception and autonomy

Compliant strain sensors are crucial for soft robots' perception and autonomy. However, their deformable bodies and dynamic actuation pose challenges in predictive sensor manufacturing and long-term robustness. This necessitates accurate sensor modelling and well-controlled sensor structural changes under strain. Here, we present a computational sensor design featuring a programmed crack array within micro-crumples strategy. By controlling the user-defined structure, the sensing performance becomes highly tunable and can be accurately modelled by physical models. Moreover, they maintain robust responsiveness under various demanding conditions including noise interruptions (50% strain), intermittent cyclic loadings (100,000 cycles), and dynamic frequencies (0-23 Hz), satisfying soft robots of diverse scaling from macro to micro. Finally, machine intelligence is applied to a sensor-integrated origami robot, enabling robotic trajectory prediction (<4% error) and topographical altitude awareness (<10% error). This strategy holds promise for advancing soft robotic capabilities in exploration, rescue operations, and swarming behaviors in complex environments.

Piezoelectric Hydrogels: Hybrid Material Design, Properties, and Biomedical Applications

Hydrogels show great potential in biomedical applications due to their inherent biocompatibility, high water content, and resemblance to the extracellular matrix. However, they lack self-powering capabilities and often necessitate external stimulation to initiate cell regenerative processes. In contrast, piezoelectric materials offer self-powering potential but tend to compromise flexibility. To address this, creating a novel hybrid biomaterial of piezoelectric hydrogels (PHs), which combines the advantageous properties of both materials, offers a systematic solution to the challenges faced by these materials when employed separately. Such innovative material system is expected to broaden the horizons of biomedical applications, such as piezocatalytic medicinal and health monitoring applications, showcasing its adaptability by endowing hydrogels with piezoelectric properties. Unique functionalities, like enabling self-powered capabilities and inducing electrical stimulation that mimics endogenous bioelectricity, can be achieved while retaining hydrogel matrix advantages. Given the limited reported literature on PHs, here recent strategies concerning material design and fabrication, essential properties, and distinctive applications are systematically discussed. The review is concluded by providing perspectives on the remaining challenges and the future outlook for PHs in the biomedical field. As PHs emerge as a rising star, a comprehensive exploration of their potential offers insights into the new hybrid biomaterials.

Biomimetic Wearable Sensors: Emerging Combination of Intelligence and Electronics

Owing to the advancement of interdisciplinary concepts, for example, wearable electronics, bioelectronics, and intelligent sensing, during the microelectronics industrial revolution, nowadays, extensively mature wearable sensing devices have become new favorites in the noninvasive human healthcare industry. The combination of wearable sensing devices with bionics is driving frontier developments in various fields, such as personalized medical monitoring and flexible electronics, due to the superior biocompatibilities and diverse sensing mechanisms. It is noticed that the integration of desired functions into wearable device materials can be realized by grafting biomimetic intelligence. Therefore, herein, the mechanism by which biomimetic materials satisfy and further enhance system functionality is reviewed. Next, wearable artificial sensory systems that integrate biomimetic sensing into portable sensing devices are introduced, which have received significant attention from the industry owing to their novel sensing approaches and portabilities. To address the limitations encountered by important signal and data units in biomimetic wearable sensing systems, two paths forward are identified and current challenges and opportunities are presented in this field. In summary, this review provides a further comprehensive understanding of the development of biomimetic wearable sensing devices from both breadth and depth perspectives, offering valuable guidance for future research and application expansion of these devices.

Rational Design of Flexible Mechanical Force Sensors for Healthcare and Diagnosis

Over the past decade, there has been a significant surge in interest in flexible mechanical force sensing devices and systems. Tremendous efforts have been devoted to the development of flexible mechanical force sensors for daily healthcare and medical diagnosis, driven by the increasing demand for wearable/portable devices in long-term healthcare and precision medicine. In this review, we summarize recent advances in diverse categories of flexible mechanical force sensors, covering piezoresistive, capacitive, piezoelectric, triboelectric, magnetoelastic, and other force sensors. This review focuses on their working principles, design strategies and applications in healthcare and diagnosis, with an emphasis on the interplay among the sensor architecture, performance, and application scenario. Finally, we provide perspectives on the remaining challenges and opportunities in this field, with particular discussions on problem-driven force sensor designs, as well as developments of novel sensor architectures and intelligent mechanical force sensing systems.

Artificial Neuron Devices

Efforts to design devices emulating complex cognitive abilities and response processes of biological systems have long been a coveted goal. Recent advancements in flexible electronics, mirroring human tissue's mechanical properties, hold significant promise. Artificial neuron devices, hinging on flexible artificial synapses, bioinspired sensors, and actuators, are meticulously engineered to mimic the biological systems. However, this field is in its infancy, requiring substantial groundwork to achieve autonomous systems with intelligent feedback, adaptability, and tangible problem-solving capabilities. This review provides a comprehensive overview of recent advancements in artificial neuron devices. It starts with fundamental principles of artificial synaptic devices and explores artificial sensory systems, integrating artificial synapses and bioinspired sensors to replicate all five human senses. A systematic presentation of artificial nervous systems follows, designed to emulate fundamental human nervous system functions. The review also discusses potential applications and outlines existing challenges, offering insights into future prospects. We aim for this review to illuminate the burgeoning field of artificial neuron devices, inspiring further innovation in this captivating area of research.

Giant Piezoelectric Output and Stability Enhancement in Piezopolymer Composites with Liquid Metal Nanofillers

Integrating nanomaterials into the polymer matrix is an effective strategy to optimize the performance of polymer-based piezoelectric devices. Nevertheless, the trade-off between the output enhancement and stability maintenance of piezoelectric composites usually leads to an unsatisfied overall performance for the high-strength operation of devices. Here, by setting liquid metal (LM) nanodroplets as the nanofillers in a poly(vinylidene difluoride) (PVDF) matrix, the as-formed liquid-solid/conductive-dielectric interfaces significantly promote the piezoelectric output and the reliability of this piezoelectric composite. A giant performance improvement featured is obtained with, nearly 1000% boosting on the output voltage (as high as 212 V), 270% increment on the piezoelectric coefficient (d33 ∼51.1 pC N-1 ) and long-term reliability on both structure and output (over 36 000 cycles). The design of a novel heterogenous interface with both mechanical matching and electric coupling can be the new orientation for developing high performance piezoelectric composite-based devices.

A Broad Range Triboelectric Stiffness Sensor for Variable Inclusions Recognition

With the development of artificial intelligence, stiffness sensors are extensively utilized in various fields, and their integration with robots for automated palpation has gained significant attention. This study presents a broad range self-powered stiffness sensor based on the triboelectric nanogenerator (Stiff-TENG) for variable inclusions in soft objects detection. The Stiff-TENG employs a stacked structure comprising an indium tin oxide film, an elastic sponge, a fluorinated ethylene propylene film with a conductive ink electrode, and two acrylic pieces with a shielding layer. Through the decoupling method, the Stiff-TENG achieves stiffness detection of objects within 1.0 s. The output performance and characteristics of the TENG for different stiffness objects under 4 mm displacement are analyzed. The Stiff-TENG is successfully used to detect the heterogeneous stiffness structures, enabling effective recognition of variable inclusions in soft object, reaching a recognition accuracy of 99.7%. Furthermore, its adaptability makes it well-suited for the detection of pathological conditions within the human body, as pathological tissues often exhibit changes in the stiffness of internal organs. This research highlights the innovative applications of TENG and thereby showcases its immense potential in healthcare applications such as palpation which assesses pathological conditions based on organ stiffness.

A Review of Epidermal Flexible Pressure Sensing Arrays

In recent years, flexible pressure sensing arrays applied in medical monitoring, human-machine interaction, and the Internet of Things have received a lot of attention for their excellent performance. Epidermal sensing arrays can enable the sensing of physiological information, pressure, and other information such as haptics, providing new avenues for the development of wearable devices. This paper reviews the recent research progress on epidermal flexible pressure sensing arrays. Firstly, the fantastic performance materials currently used to prepare flexible pressure sensing arrays are outlined in terms of substrate layer, electrode layer, and sensitive layer. In addition, the general fabrication processes of the materials are summarized, including three-dimensional (3D) printing, screen printing, and laser engraving. Subsequently, the electrode layer structures and sensitive layer microstructures used to further improve the performance design of sensing arrays are discussed based on the limitations of the materials. Furthermore, we present recent advances in the application of fantastic-performance epidermal flexible pressure sensing arrays and their integration with back-end circuits. Finally, the potential challenges and development prospects of flexible pressure sensing arrays are discussed in a comprehensive manner.

Soft Robotics Enables Neuroprosthetic Hand Design

Development and implementation of neuroprosthetic hands is a multidisciplinary field at the interface between humans and artificial robotic systems, which aims at replacing the sensorimotor function of the upper-limb amputees as their own. Although prosthetic hand devices with myoelectric control can be dated back to more than 70 years ago, their applications with anthropomorphic robotic mechanisms and sensory feedback functions are still at a relatively preliminary and laboratory stage. Nevertheless, a recent series of proof-of-concept studies suggest that soft robotics technology may be promising and useful in alleviating the design complexity of the dexterous mechanism and integration difficulty of multifunctional artificial skins, in particular, in the context of personalized applications. Here, we review the evolution of neuroprosthetic hands with the emerging and cutting-edge soft robotics, covering the soft and anthropomorphic prosthetic hand design and relating bidirectional neural interactions with myoelectric control and sensory feedback. We further discuss future opportunities on revolutionized mechanisms, high-performance soft sensors, and compliant neural-interaction interfaces for the next generation of neuroprosthetic hands.

Balanced Coexistence of Reversible and Irreversible Covalent Bonds in a Conductive Triple Polymeric Network Enables Stretchable Hydrogels with High Toughness and Adhesiveness

The application of soft hydrogels to stretchable devices has attracted increasing attention in deformable bioelectronics owing to their unique characteristic, "modulus matching between materials and organs". Despite considerable progress, their low toughness, low conductivity, and absence of tissue adhesiveness remain substantial challenges associated with unstable skin-interfacing, where body movements undesirably disturb electrical signal acquisitions. Herein, we report a material design of a highly tough strain-dissipative and skin-adhesive conducting hydrogel fabricated through a facile one-step sol-gel transition and its application to an interactive human-machine interface. The hydrogel comprises a triple polymeric network where irreversible amide linkage of polyacrylamide with alginate and dynamic covalent bonds entailing conjugated polymer chains of poly(3,4-ethylenedioxythiophene)-co-(3-thienylboronic acid) are simultaneously capable of high stretchability (1300% strain), efficient strain dissipation (36,209 J/m²), low electrical resistance (590 Ω), and even robust skin adhesiveness (35.0 ± 5.6 kPa). Based on such decent characteristics, the hydrogel was utilized as a multifunctional layer for successfully performing either electrophysiological cardiac/muscular on-skin sensors or an interactive stretchable human-machine interface.

Transparent, Ultra-Stretching, Tough, Adhesive Carboxyethyl Chitin/Polyacrylamide Hydrogel Toward High-Performance Soft Electronics

To date, hydrogels have gained increasing attentions as a flexible conductive material in fabricating soft electronics. However, it remains a big challenge to integrate multiple functions into one gel that can be used widely under various conditions. Herein, a kind of multifunctional hydrogel with a combination of desirable characteristics, including remarkable transparency, high conductivity, ultra-stretchability, toughness, good fatigue resistance, and strong adhesive ability is presented, which was facilely fabricated through multiple noncovalent crosslinking strategy. The resultant versatile sensors are able to detect both weak and large deformations, which owns a low detection limit of 0.1% strain, high stretchability up to 1586%, ultrahigh sensitivity with a gauge factor up to 18.54, as well as wide pressure sensing range (0-600 kPa). Meanwhile, the fabrication of conductive hydrogel-based sensors is demonstrated for various soft electronic devices, including a flexible human-machine interactive system, the soft tactile switch, an integrated electronic skin for unprecedented nonplanar visualized pressure sensing, and the stretchable triboelectric nanogenerators with excellent biomechanical energy harvesting ability. This work opens up a simple route for multifunctional hydrogel and promises the practical application of soft and self-powered wearable electronics in various complex scenes.

Freestanding and Scalable Force-Softness Bimodal Sensor Arrays for Haptic Body-Feature Identification

Tactile technologies that can identify human body features are valuable in clinical diagnosis and human-machine interactions. Previously, cutting-edge tactile platforms have been able to identify structured non-living objects; however, identification of human body features remains challenging mainly because of the irregular contour and heterogeneous spatial distribution of softness. Here, freestanding and scalable tactile platforms of force-softness bimodal sensor arrays are developed, enabling tactile gloves to identify body features using machine-learning methods. The bimodal sensors are engineered by adding a protrusion on a piezoresistive pressure sensor, endowing the resistance signals with combined information of pressure and the softness of samples. The simple design enables 112 bimodal sensors to be integrated into a thin, conformal, and stretchable tactile glove, allowing the tactile information to be digitalized while hand skills are performed on the human body. The tactile glove shows high accuracy (98%) in identifying four body features of a real person, and four organ models (healthy and pathological) inside an abdominal simulator, demonstrating identification of body features of the bimodal tactile platforms and showing their potential use in future healthcare and robotics.

Dual sensing signal decoupling based on tellurium anisotropy for VR interaction and neuro-reflex system application

Anisotropy control of the electronic structure in inorganic semiconductors is an important step in developing devices endowed with multi-function. Here, we demonstrate that the intrinsic anisotropy of tellurium nanowires can be used to modulate the electronic structure and piezoelectric polarization and decouple pressure and temperature difference signals, and realize VR interaction and neuro-reflex applications. The architecture design of the device combined with self-locking effect can eliminate dependence on displacement, enabling a single device to determine the hardness and thermal conductivity of materials through a simple touch. We used a bimodal Te-based sensor to develop a wearable glove for endowing real objects to the virtual world, which greatly improves VR somatosensory feedback. In addition, we successfully achieved stimulus recognition and neural-reflex in a rabbit sciatic nerve model by integrating the sensor signals using a deep learning technique. In view of in-/ex-vivo feasibility, the bimodal Te-based sensor would be considered a novel sensing platform for a wide range application of metaverse, AI robot, and electronic medicine.

The accumulation of single-function sensors can increase the complexity of virtual reality systems. Here, Shen et al. exploit the intrinsic anisotropy of tellurium nanowires to design a multi-function pressure and temperature sensor, which can be used as tactile experience in the virtual world.

A flexible metal nano-mesh strain sensor with the characteristic of spontaneous functional recovery after fracture damage

Developing flexible sensors with high sensitivity, a wide sensing range, and good stability is a challenge. By replicating the anodic aluminum oxide (AAO) hole structure, we proposed new strain sensors with Pt nano-mesh films embedded in polydimethylsiloxane (PDMS) films. The nano-mesh strain sensor exhibited high sensitivity (a gauge factor of 4500) and a sensing range as high as 90%. The resistance remained almost completely unchanged after 1500 loading/unloading cycles of 15% strain, demonstrating the high repeatability and stability of the sensor. In addition, even if the nano-mesh experienced an open circuit by overstraining, the sensor can still measure strain within 45% after recovery. The capability of spontaneous functional recovery after fractural damage considerably extends its service life. Finally, the nano-mesh strain sensors were worn on the wrist and neck to monitor wrist movement and throat vibration, respectively. Signals corresponding to swallowing, throat clearing, and letter pronunciation were clearly distinguished from the peak value and signal patterns. These results indicate that the metal nano-mesh strain sensors have great potential for applications in wearable devices, electronic skin, and flexible robotics.

High-Stretchability, Ultralow-Hysteresis ConductingPolymer Hydrogel Strain Sensors for Soft Machines

Highly stretchable strain sensors based on conducting polymer hydrogel are rapidly emerging as a promising candidate toward diverse wearable skins and sensing devices for soft machines. However, due to the intrinsic limitations of low stretchability and large hysteresis, existing strain sensors cannot fully exploit their potential when used in wearable or robotic systems. Here, a conducting polymer hydrogel strain sensor exhibiting both ultimate strain (300%) and negligible hysteresis (<1.5%) is presented. This is achieved through a unique microphase semiseparated network design by compositing poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) nanofibers with poly(vinyl alcohol) (PVA) and facile fabrication by combining 3D printing and successive freeze-thawing. The overall superior performances of the strain sensor including stretchability, linearity, cyclic stability, and robustness against mechanical twisting and pressing are systematically characterized. The integration and application of such strain sensor with electronic skins are further demonstrated to measure various physiological signals, identify hand gestures, enable a soft gripper for objection recognition, and remote control of an industrial robot. This work may offer both promising conducting polymer hydrogels with enhanced sensing functionalities and technical platforms toward stretchable electronic skins and intelligent robotic systems.

Recent advances in microsystem approaches for mechanical characterization of soft biological tissues

Microsystem technologies for evaluating the mechanical properties of soft biological tissues offer various capabilities relevant to medical research and clinical diagnosis of pathophysiologic conditions. Recent progress includes (1) the development of tissue-compliant designs that provide minimally invasive interfaces to soft, dynamic biological surfaces and (2) improvements in options for assessments of elastic moduli at spatial scales from cellular resolution to macroscopic areas and across depths from superficial levels to deep geometries. This review summarizes a collection of these technologies, with an emphasis on operational principles, fabrication methods, device designs, integration schemes, and measurement features. The core content begins with a discussion of platforms ranging from penetrating filamentary probes and shape-conformal sheets to stretchable arrays of ultrasonic transducers. Subsequent sections examine different techniques based on planar microelectromechanical system (MEMS) approaches for biocompatible interfaces to targets that span scales from individual cells to organs. One highlighted example includes miniature electromechanical devices that allow depth profiling of soft tissue biomechanics across a wide range of thicknesses. The clinical utility of these technologies is in monitoring changes in tissue properties and in targeting/identifying diseased tissues with distinct variations in modulus. The results suggest future opportunities in engineered systems for biomechanical sensing, spanning a broad scope of applications with relevance to many aspects of health care and biology research.

Highly-integrated, miniaturized, stretchable electronic systems based on stacked multilayer network materials

Elastic stretchability and function density represent two key figures of merits for stretchable inorganic electronics. Various design strategies have been reported to provide both high levels of stretchability and function density, but the function densities are mostly below 80%. While the stacked device layout can overcome this limitation, the soft elastomers used in previous studies could highly restrict the deformation of stretchable interconnects. Here, we introduce stacked multilayer network materials as a general platform to incorporate individual components and stretchable interconnects, without posing any essential constraint to their deformations. Quantitative analyses show a substantial enhancement (e.g., by ~7.5 times) of elastic stretchability of serpentine interconnects as compared to that based on stacked soft elastomers. The proposed strategy allows demonstration of a miniaturized electronic system (11 mm by 10 mm), with a moderate elastic stretchability (~20%) and an unprecedented areal coverage (~110%), which can serve as compass display, somatosensory mouse, and physiological-signal monitor.

Mechanically Durable Memristor Arrays Based on a Discrete Structure Design

Memristors constitute a promising functional component for information storage and in-memory computing in flexible and stretchable electronics including wearable devices, prosthetics, and soft robotics. Despite tremendous efforts made to adapt conventional rigid memristors to flexible and stretchable scenarios, stretchable and mechanical-damage-endurable memristors, which are critical for maintaining reliable functions under unexpected mechanical attack, have never been achieved. Here, the development of stretchable memristors with mechanical damage endurance based on a discrete structure design is reported. The memristors possess large stretchability (40%) and excellent deformability (half-fold), and retain stable performances under dynamic stretching and releasing. It is shown that the memristors maintain reliable functions and preserve information after extreme mechanical damage, including puncture (up to 100 times) and serious tearing situations (fully diagonally cut). The structural strategy offers new opportunities for next-generation stretchable memristors with mechanical damage endurance, which is vital to achieve reliable functions for flexible and stretchable electronics even in extreme and highly dynamic environments.

Artificial Sense Technology: Emulating and Extending Biological Senses

Biological senses are critical for the survival of organisms. A great deal of attention has focused on elucidating the underlying physiological mechanisms of the senses, inspiring various sensing techniques. Despite progress in this area, gaps remain between the biological senses and conventional sensing techniques. In this Perspective, we propose the concept of artificial sense technology, which mimics the biological senses but differs in terms of objective sensing and intelligent feedback capabilities. We first summarize recent progress in the use of nanotechnologies to emulate the biological senses and then outline the advantages of artificial sense technology, which extend the capabilities of its biological counterparts. We envision artificial sense technology as a powerful perceptual interface that will play key roles in sensation substitution, digital healthcare, animal interactions, plant electronics, smart robots, and other areas that enrich the connections of the physical and virtual worlds.